Because of all the confusion around the technology, it’s easy to miss all the positive impact artificial intelligence (AI) is already having on our world. In reality, many aspects of AI like computer vision (CV),have already changed multiple industries for the better, helping businesses and organizations to improve the lives of people worldwide. Below, I’ll outline 5 industries that have seen computer vision optimize and revolutionize the way they serve humans.
With self-driving cars attracting so much attention, no industry has become more well-known for its application of AI than the car industry. Many controversies still surround the innovation, but thanks to computer vision cars on the whole are getting safer.
Many driver assistance systems utilize CV to detect traffic signs or road lanes, potentially preventing drivers from having accidents caused by drifting. Similarly, parking assistance systems use CV to help drivers as they drive or back into parking spaces by detecting the objects behind or in front of the vehicle and warning them if the driver is too close.
And computer vision isn’t just being used in the cars themselves. Now, the technology is even helping manufacturers to better and more quickly identify defective parts, reducing the risk of them going on the road, making things even safer.
Agriculture has changed a lot in the thousands of years since humans began to cultivate the land, and farmers continue to innovate -- now with computer vision. Cattle rearers, for instance, are looking at using facial recognition to identify individual animals within a herd, allowing for better herd monitoring with less human intervention. It’s making for better food as well. Produce growers for some of the leading grocers around the world, including Walmart, are using computer vision to better detect pests and plant diseases in their crops. Further, they’re able to learn more about their plants in general and grow higher-quality crops with more efficiency for their consumers.
3. Food & Beverage
Quality assurance inspectors have one of the most crucial jobs in the food and beverage manufacturing industry. However, relying on manual checks increases the chances of them missing things like bugs or shards of glass as products move along the conveyor belt. With computer vision, these dangerous foreign objects can be identified before products are sent to a distributor. Manufacturers also use computer vision to estimate the freshness of their products, so everything that leaves their facilities is at the most optimal quality.
With drivers travelling at upwards of 200 miles per hour, fatalities in motorsports like car racing seem inevitable. Nascar has implemented many safety measures to protect drivers since the untimely death of world-famous race car driver Dale Earnhardt in 2001 and no further fatalities have occurred.
Still, crashes continue, resulting in significant costs and potential death, so Nascar remains vigilant. Using computer vision, they’re now trying to address the danger associated with malfunctioning cars. Utilizing its extensive data set, the company was able to train a deep learning neural network to identify specific race cars. Even with blurry images of speeding cars, the model worked faster and better than humans.
This proficiency is expected to allow the trained network to quickly identify and access whether a race car is having a problem, which could be fateful in being able to quickly diffuse potential hazards and save drivers’ lives.
As many parts of the world are so isolated, that their populaces have no access to basic healthcare or the internet. Since CV utilizes the internet, one might assume its usefulness in healthcare is limited to more centralized or “developed” locations. Companies like i-Nside challenge this notion. A world leader in endoscopic technology, i-Nside’s mission is to use AI to develop tools “that will fundamentally increase the access to diagnostics in remote areas.”
Using Clarifai’s CV technology and mobile software development kit (SDK), i-Nside was able to leverage CV’s capabilities to build an app that could help doctors diagnose ear diseases found in patients.
When combined with their affordable smartphone attachment, doctors in even the most remote places can take medical-grade pictures of the inner ear with any smartphone and use the app to identify diseases with almost 100% accuracy or diagnose them with almost 90% accuracy, even without the internet.
Due to CV AI being used to build solutions that have made companies more efficient and profitable, we may forget the ways the technology has opened up our world. From the above, however, we can see that thanks to CV AI, the world is becoming a safer, better place.